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Updated: May 10, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
BeEP Server: Using evolutionary information for quality assessment of protein structure models.
Nicolas Palopoli1, Esteban Lanzarotti, Gustavo Parisi
1Departamento de Ciencia y Tecnologia, Universidad Nacional de Quilmes, B1876BXD, Bernal, Buenos Aires, Argentina.
The BeEP Server ranks protein structure models using evolutionary information, not just structure or energy. This method identifies native-like protein structures by analyzing evolutionary patterns in homologous proteins.
Area of Science:
- Computational Biology
- Bioinformatics
- Structural Biology
Background:
- Protein structure prediction is a complex challenge.
- Existing methods often rely on structural or energetic evaluations.
- A novel approach utilizing evolutionary information can enhance model assessment.
Purpose of the Study:
- To introduce the BeEP Server as an online resource for protein structure prediction.
- To present a new method for ranking protein structural models using evolutionary data.
- To evaluate the effectiveness of the BeEP method in identifying native-like structures.
Main Methods:
- The BeEP Server employs evolutionary information to rank protein models.
- It utilizes substitution patterns from homologous proteins to build site-specific matrices.
- Maximum likelihood calculations assess matrix suitability and derive position-specific scores.
Main Results:
- BeEP successfully discriminates between protein structural models.
- The method can select native-like structures from submitted models.
- BeEP's evolutionary approach aids in exploring the native state's conformational ensemble.
Conclusions:
- The BeEP Server offers a unique approach to protein structure model assessment.
- Evolutionary information provides a valuable criterion for ranking structural models.
- BeEP demonstrates potential for improving the accuracy and scope of protein structure prediction.
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